Tordess – Crypto's first prop-trade and social trading platform

Hacker News

Hi, I am Dat, Co-founder and CEO of https://tordess.com/ . We are crypto's first prop-trade platform (following business model of ftmo.com and topstep.com, originally for forex & stocks). Our vision is to become a leading crypto social trading platform that offers both prop-trade challenge and copy-trade (twisting Etoro's business model by combining prop-trade + copy-trade to fit the volatility of crypto markets). The problem? There is a huge demand for social trading (similar to Etoro) from crypto traders. However, due to the volatile nature of crypto markets, crypto social trading platforms that blindly follow Etoro model do not work. Most copiers there do not gain sustainable profit by copying the top traders but are exposed to significant drawdown risk. Why Tordess? Combining prop-trade challenges and copy-trade functions can solve the above problem. Being the first prop-trade + copy-trade platform for crypto, we are combining 2 proven business models in stock & forex trading, apply into crypto trading with the aim to disrupt the status quo in its social trading segment. Our progress? We launched our MVP (open-beta) on October 15th, acquired close to 200 beta users/testers as of today and secured affiliate partnership with 2 major Vietnamese crypto trading & prop-trade (Facebook) groups that have more than 200 thousands members. What we are asking for? Feedback, advice, thoughts, comments, anything that helps us serve crypto traders better. Join our free monthly competition to try it out. A good number of skilled crypto day-traders are fighting for the top 3 spots in the leaderboard.

Visit product View on Hacker NewsOct 20, 2022

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Actual performance

2points

Did not reach leaderboard

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

80%80% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

TrustMRRFits verified-revenue profile · Strong signals: month, monthly, users · Missing: mobile apps, ios, personal

61%61% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoStrong fit for a featured deal · Strong signals: platform, users · Missing: plus, intuitive, reviews

52%52% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released

40%40% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Acquire.comPre-revenue stage for this audience · Strong signals: profit · Missing: arr, mrr, revenue

17%17% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Strong signals: model, user, models · Missing: mac, agents, macos

10%10% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: crypto · Missing: web3, chat, cryptocurrency

5%5% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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